Cargando…

An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity

Aim To investigate reliability of the Easy IOTN app between clinicians with different levels of experience in determining Index of Orthodontic Treatment Need (IOTN) Dental Health Component (DHC) and Aesthetic Component (AC) scores from study models. The accuracy of each clinician in discriminating t...

Descripción completa

Detalles Bibliográficos
Autores principales: Nandra, Sukbir, Crawford, Nicola, Burford, Daniel, Pandis, Nikolaos, Cobourne, Martyn T., Seehra, Jadbinder
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142362/
https://www.ncbi.nlm.nih.gov/pubmed/35624263
http://dx.doi.org/10.1038/s41415-022-4246-2
_version_ 1784715558718013440
author Nandra, Sukbir
Crawford, Nicola
Burford, Daniel
Pandis, Nikolaos
Cobourne, Martyn T.
Seehra, Jadbinder
author_facet Nandra, Sukbir
Crawford, Nicola
Burford, Daniel
Pandis, Nikolaos
Cobourne, Martyn T.
Seehra, Jadbinder
author_sort Nandra, Sukbir
collection PubMed
description Aim To investigate reliability of the Easy IOTN app between clinicians with different levels of experience in determining Index of Orthodontic Treatment Need (IOTN) Dental Health Component (DHC) and Aesthetic Component (AC) scores from study models. The accuracy of each clinician in discriminating treatment need using the app against the 'gold standard' conventional assessment at the threshold of treatment acceptance criteria was also explored. Materials and methods In total, 150 sets of pre-treatment study models were assessed by six clinicians using the app on two separate occasions (T1 and T2). A single IOTN-calibrated clinician also scored the models using the conventional technique. Clinician scores for both intra- and inter-rater reliability were assessed using Cohen's Kappa. The performance of each clinician in discriminating treatment need using the app against the conventional assessment method at the threshold of treatment acceptance criteria was also assessed using the area under the curve-receiver operating characteristic. Results The intra-rater agreement for the clinician undertaking the conventional assessment of the models was 1.0. Intra-rater agreement scores for clinicians using the Easy IOTN app ranged between 0.37-0.87 (DHC) and 0.22-0.44 (AC). Inter-rater agreement scores at T2 were 0.59 (DHC) and 0.23 (AC). Based on the IOTN DHC, all clinicians displayed an excellent level of accuracy in determining malocclusions qualifying for treatment (range 81.7-90.0%). Based on the IOTN AC, all clinicians showed an acceptable level of accuracy in determining malocclusions qualifying for treatment (range 71.9-79.2%). Conclusions The Easy IOTN app was shown to have moderate inter-rater reliability. Variation in the intra-rater reliability was evident between clinicians of different grades/level of experience. Importantly, the diagnostic accuracy of the app to discriminate between malocclusions that qualify for NHS treatment was rated as excellent (IOTN DHC) and acceptable (IOTN AC) and independent of clinician grade or level of experience.
format Online
Article
Text
id pubmed-9142362
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-91423622022-05-29 An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity Nandra, Sukbir Crawford, Nicola Burford, Daniel Pandis, Nikolaos Cobourne, Martyn T. Seehra, Jadbinder Br Dent J Research Aim To investigate reliability of the Easy IOTN app between clinicians with different levels of experience in determining Index of Orthodontic Treatment Need (IOTN) Dental Health Component (DHC) and Aesthetic Component (AC) scores from study models. The accuracy of each clinician in discriminating treatment need using the app against the 'gold standard' conventional assessment at the threshold of treatment acceptance criteria was also explored. Materials and methods In total, 150 sets of pre-treatment study models were assessed by six clinicians using the app on two separate occasions (T1 and T2). A single IOTN-calibrated clinician also scored the models using the conventional technique. Clinician scores for both intra- and inter-rater reliability were assessed using Cohen's Kappa. The performance of each clinician in discriminating treatment need using the app against the conventional assessment method at the threshold of treatment acceptance criteria was also assessed using the area under the curve-receiver operating characteristic. Results The intra-rater agreement for the clinician undertaking the conventional assessment of the models was 1.0. Intra-rater agreement scores for clinicians using the Easy IOTN app ranged between 0.37-0.87 (DHC) and 0.22-0.44 (AC). Inter-rater agreement scores at T2 were 0.59 (DHC) and 0.23 (AC). Based on the IOTN DHC, all clinicians displayed an excellent level of accuracy in determining malocclusions qualifying for treatment (range 81.7-90.0%). Based on the IOTN AC, all clinicians showed an acceptable level of accuracy in determining malocclusions qualifying for treatment (range 71.9-79.2%). Conclusions The Easy IOTN app was shown to have moderate inter-rater reliability. Variation in the intra-rater reliability was evident between clinicians of different grades/level of experience. Importantly, the diagnostic accuracy of the app to discriminate between malocclusions that qualify for NHS treatment was rated as excellent (IOTN DHC) and acceptable (IOTN AC) and independent of clinician grade or level of experience. Nature Publishing Group UK 2022-05-27 2022 /pmc/articles/PMC9142362/ /pubmed/35624263 http://dx.doi.org/10.1038/s41415-022-4246-2 Text en © The Author(s) 2022, © British Dental Association 2022, corrected publication 2022. https://creativecommons.org/licenses/by/4.0/Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) .© The Author(s) 2022
spellingShingle Research
Nandra, Sukbir
Crawford, Nicola
Burford, Daniel
Pandis, Nikolaos
Cobourne, Martyn T.
Seehra, Jadbinder
An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title_full An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title_fullStr An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title_full_unstemmed An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title_short An investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
title_sort investigation into the reliability of a mobile app designed to assess orthodontic treatment need and severity
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142362/
https://www.ncbi.nlm.nih.gov/pubmed/35624263
http://dx.doi.org/10.1038/s41415-022-4246-2
work_keys_str_mv AT nandrasukbir aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT crawfordnicola aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT burforddaniel aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT pandisnikolaos aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT cobournemartynt aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT seehrajadbinder aninvestigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT nandrasukbir investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT crawfordnicola investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT burforddaniel investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT pandisnikolaos investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT cobournemartynt investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity
AT seehrajadbinder investigationintothereliabilityofamobileappdesignedtoassessorthodontictreatmentneedandseverity